Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition

age-estimation body-segmentation body-tracking emotion-detection face-detection face-matching face-mesh face-position face-recognition faceid gaze-tracking gender-prediction gesture-recognition hand-tracking iris-tracking tensorflowjs tfjs

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README.md

Human Library

3D Face Detection, Face Embedding & Recognition,
Body Pose Tracking, Hand & Finger Tracking,
Iris Analysis, Age & Gender & Emotion Prediction
& Gesture Recognition

Native JavaScript module using TensorFlow/JS Machine Learning library
Compatible with Browser, WebWorker and NodeJS execution on both Windows and Linux

Browser/WebWorker: Compatible with CPU, WebGL, WASM and WebGPU backends
NodeJS: Compatible with software tfjs-node and CUDA accelerated backends tfjs-node-gpu

Check out Live Demo for processing of live WebCam video or static images

Project pages

Wiki pages

Additional notes

Default models

Default models in Human library are:

Face Detection: MediaPipe BlazeFace-Back
Face Mesh: MediaPipe FaceMesh
Face Iris Analysis: MediaPipe Iris
Emotion Detection: Oarriaga Emotion
Gender Detection: Oarriaga Gender
Age Detection: SSR-Net Age IMDB
Body Analysis: PoseNet
Face Embedding: Sirius-AI MobileFaceNet Embedding

Note that alternative models are provided and can be enabled via configuration
For example, PoseNet model can be switched for BlazePose model depending on the use case

For more info, see Configuration Details and List of Models

See issues and discussions for list of known limitations and planned enhancements

Suggestions are welcome!

Options

As presented in the demo application...

Examples

Training image:

Using static images:

Live WebCam view: